A camera calibration method for large field optical measurement

Shang, Yang; Sun, Xiangyi; Yang, X. H.; Wang, Xi; Yu, Qifeng

doi:10.1016/j.ijleo.2013.05.121

Cited by 25 publications

(16 citation statements)

References 10 publications

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“…Finally, based on the initial values of the camera parameters, their precise values are calculated by using bundle adjustment optimization. More details can be found in the work by Shang et al 16 A multirotor UAV and a prism are shown in Figure 2(b). The multirotor UAV can make a flexible motion, and the prism is mounted underneath the UAV, which is used to reflect the laser light.…”

Section: Condition Shang Et Al's Methodsmentioning

confidence: 99%

“…Because the cameras often need to adjust the depth of field and installation angle, etc., according to the actual measurement task, calibrating the camera parameters in the laboratory in advance is not suitable. 16 It is necessary to calibrate the camera parameters directly in the field, even if the FOV of the camera is void. For example, cameras that are pointing to sky cannot find any calibration objects in the FOV.…”

Section: Introductionmentioning

confidence: 99%

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Multi-camera networks for motion parameter estimation of an aircraft

Guan

Sun

Shang

et al. 2017

International Journal of Advanced Robotic Systems

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A multi-camera network is proposed to estimate an aircraft's motion parameters relative to the reference platform in large outdoor fields. Multiple cameras are arranged to cover the aircraft's large-scale motion spaces by field stitching. A camera calibration method using dynamic control points created by a multirotor unmanned aerial vehicle is presented under the conditions that the field of view of the cameras is void. The relative deformation of the camera network caused by external environmental factors is measured and compensated using a combination of cameras and laser rangefinders. A series of field experiments have been carried out using a fixed-wing aircraft without artificial makers, and its accuracy is evaluated using an onboard Differential Global Positioning System. The experimental results show that the multi-camera network is precise, robust, and highly dynamic and can improve the aircraft's landing accuracy.

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Section: Condition Shang Et Al's Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-camera networks for motion parameter estimation of an aircraft

Guan

Sun

Shang

et al. 2017

International Journal of Advanced Robotic Systems

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“…Many years, photogrammetry researchers and recently, computer vision researchers have taken camera calibration issue into consideration [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Every recently camera should be calibrated to correct its lens distortion and interior orientation elements.…”

Section: Introductionmentioning

confidence: 99%

Camera Calibration: An Overview of Concept, Methods and Equations

Saeifar¹,

Nia²

2017

IJERA

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Camera calibration is favored as an important issue in photogrammetry and computer vision literatures. The importance of this issue can be due to two reasons: firstly, every recently camera should be calibrated before being used to correct its lens distortion and interior orientation elements. In addition, it is a main preprocessing step at many vision applications. This paper aims to provide an overview of concept, objective, methods and mathematical equations for camera calibration.

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“…Camera calibration methods by using fringe patterns, not-measured calibration target, and Virtual 1D Target are also ways to simplify the procedure [10][11][12]. There have been a few efforts to solve the problem of calibration for the system with a large field of view without using a big planar target [13][14][15]. For example, Xiao etc.…”

Section: Introductionmentioning

confidence: 99%